JpGU-AGU Joint Meeting 2020

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-OS Ocean Sciences & Ocean Environment

[A-OS17] Climate variability and predictability on subseasonal to decadal timescales

convener:Takashi Mochizuki(Department of Earth and Planetary Sciences, Kyushu University), V Ramaswamy(NOAA GFDL), Yushi Morioka(Japan Agency for Marine-Earth Science and Technology)

[AOS17-03] An overview of seasonal to Decadal Predictions with MIROC6

*Takahito Kataoka1, Hiroaki Tatebe1, Hiroshi Koyama1, Takashi Mochizuki1,2, Koji Ogochi1, Hiroaki Naoe3, Yukiko Imada3, Hideo Shiogama4,5, Masahide Kimoto5, Masahiro Watanabe5 (1.JAMSTEC Japan Agency for Marine-Earth Science and Technology, 2.Kyusyu University, 3.Meteorological Research Institute, 4.National Institute for Environmental Studies, 5.The University of Tokyo)

Keywords:decadal prediction, seasonal prediction, climate variation

The study presents results of seasonal-to-decadal climate predictions based on a coupled climate model called the Model for Interdisciplinary Research on Climate version 6 (MIROC6) contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). MIROC6 is initialized every year for 1960-2018 by assimilating observed ocean temperature and salinity anomalies and full-fields of sea-ice concentration, and by prescribing atmospheric initial states from reanalysis data. The impacts of updating system on prediction skill are then evaluated by comparing hindcast experiments between the MIROC6 prediction system and a previous system based on MIROC version 5 (MIROC5).
Skill of seasonal prediction is overall improved in association with representation of El Niño/Southern Oscillation (ENSO), the Quasi-Biennial Oscillation (QBO), and the Barents-Kara sea-ice concentration in MIROC6. In particular, the QBO is skillfully predicted up to 3 years ahead with a maximum anomaly correlation exceeding r=0.8. The prediction skill for the North Atlantic Oscillation in winter is also enhanced, but the prediction still suffers from model’s inherent errors. On decadal timescales, MIROC6 has a predictive skill in the annual-mean sea surface temperature (SST) in the North Atlantic and the tropical Pacific. In particular, SST variability in the eastern tropical Pacific is predicted up to 7-10 years with a significantly larger skill score than the uninitialized experiment. MIROC6 hindcasts predict the Pacific regime shifts in the late-1970s and late-1990s better than MIROC5 hindcasts likely because of the improved skill of predicting interannual ENSO variability.